Tissue compartmentalization enables Salmonella persistence during chemotherapy

Antimicrobial chemotherapy can fail to eradicate the pathogen, even in the absence of antimicrobial resistance. Persisting pathogens can subsequently cause relapsing diseases. In vitro studies suggest various mechanisms of antibiotic persistence, but their in vivo relevance remains unclear because of the difficulty of studying scarce pathogen survivors in complex host tissues. Here, we localized and characterized rare surviving Salmonella in mouse spleen using high-resolution whole-organ tomography. Chemotherapy cleared >99.5% of the Salmonella but was inefficient against a small Salmonella subset in the white pulp. Previous models could not explain these findings: drug exposure was adequate, Salmonella continued to replicate, and host stresses induced only limited Salmonella drug tolerance. Instead, antimicrobial clearance required support of Salmonella-killing neutrophils and monocytes, and the density of such cells was lower in the white pulp than in other spleen compartments containing higher Salmonella loads. Neutrophil densities declined further during treatment in response to receding Salmonella loads, resulting in insufficient support for Salmonella clearance from the white pulp and eradication failure. However, adjunctive therapies sustaining inflammatory support enabled effective clearance. These results identify uneven Salmonella tissue colonization and spatiotemporal inflammation dynamics as main causes of Salmonella persistence and establish a powerful approach to investigate scarce but impactful pathogen subsets in complex host environments.

In difficult-to-treat bacterial infections, including tuberculosis, deep-seated Staphylococcus aureus infections, and invasive salmonellosis, adequate antimicrobial chemotherapy can initially clear most pathogen cells and resolve clinical symptoms. However, even extended therapy often fails to eradicate the pathogen, even in the absence of relevant antimicrobial resistance. The persistence of a small subset of pathogen cells can cause relapsing diseases and accelerates the emergence of antimicrobial resistance (1–4). Eradication of such difficult-to-treat infections represents an urgent medical need.Development of effective treatments requires a detailed understanding of the underlying mechanisms. Various mechanisms have been proposed to explain pathogen persistence during antimicrobial chemotherapy. First, antimicrobials might not reach all bacterial cells in sufficient amounts because anatomical permeation barriers limit drug access to bacteria in certain tissue areas (5, 6). Second, bacteria might adopt physiological states in host tissues that enable them to tolerate antibiotic exposure. Such tolerant states might be triggered by stresses imposed on the pathogen by the host immune system (7–13). Moreover, limited nutrient supply and stress conditions can slow bacterial proliferation, which increases tolerance to most antibiotics (14–18), in some conditions due to low ATP levels (19). Third, pathogen heterogeneity has been suggested as a major cause of treatment failures (1, 2, 20–22). Some bacteria might stop replication either because of stochastic internal processes or in response to external triggers. Such nonreplicating “persisters” can survive exposure to otherwise lethal antibiotic concentrations. Other forms of heterogeneity might also contribute to treatment failures, including asymmetric cell division (23–25), uneven partitioning of efflux pumps among daughter cells (26), heterogeneous expression of prodrug-activating enzymes (27), transient gene amplification (28), and heterogeneous induction of specific stress responses (29). The relevance of these various mechanisms for pathogen persistence in host tissues remains unclear because supporting data have been obtained almost exclusively using in vitro models (1–3, 20–22, 30). In vivo data are critical because bacterial susceptibility depends on environmental factors, and complex and diverse microenvironments in infected tissues are difficult to mimic in vitro (31).One suitable small-animal infection model for in vivo studies is systemic salmonellosis in mice as a model for human invasive Salmonella infections. Such infections, including typhoid and paratyphoid fever (enteric fever) as well as nontyphoidal Salmonella (NTS) bacteremia, are a major health problem worldwide (32, 33). Antimicrobial chemotherapy frequently fails to eradicate Salmonella, resulting in relapsing disease, even when the bacterial strain is susceptible to the drug (34–37). Mouse models of invasive salmonellosis recapitulate these eradication challenges (38–41). We showed previously that clinically relevant doses of fluoroquinolone antibiotics clear Salmonella from mouse tissues only slowly because Salmonella replicates slowly in vivo with generation times around 6.5 h (42). Nevertheless, clearance continues with a monophasic exponential decay of colony-forming units (CFUs) for at least 5 d. Here, we continued treatment for longer intervals and observed declining clearance rates and eradication failure at later time points. We aimed at unraveling the mechanisms underlying this antibiotic persistence of Salmonella.In vivo studies of pathogen cells surviving chemotherapy have been thwarted by difficulties in localizing and characterizing few, sparsely distributed, micrometer-sized pathogen cells in entire centimeter-sized host organs. We addressed these limitations by adopting serial two-photon tomography (STP) (43) for detecting individual Salmonella cells across entire spleens of infected mice. We resolved interfering tissue autofluorescence, developed automated pipelines for identifying Salmonella cells in terabytes (TB) of imaging data, and validated accurate detection of single Salmonella cells at densities as low as one bacterium in 100 mm³ tissue. We used STP to localize Salmonella surviving treatment with two clinically relevant antibiotic classes. We combined STP with laser-capture microdissection, flow cytometry, Salmonella reporter constructs, and adjunctive therapies, to determine the relevance of nonreplicating Salmonella persisters, stress-triggered drug tolerance, uneven drug delivery, and tissue infiltration by neutrophils and inflammatory monocytes. We found that Salmonella colonization of spleen in untreated mice was inhomogeneous. A minor Salmonella subset colonized the white pulp (WP) and triggered only limited local infiltration of inflammatory monocytes and neutrophils. These Salmonella-killing host cells supported Salmonella clearance during chemotherapy, but their density collapsed during chemotherapy in response to receding local Salmonella loads resulting in 70-fold better Salmonella survival in the WP compared to other, initially more colonized and inflamed spleen compartments. By contrast, Salmonella dormancy, stress-induced antimicrobial tolerance, or inefficient antibiotic delivery had all minor relevance. Thus, host tissue architecture and the topology and dynamics of host–Salmonella interactions caused locally divergent antimicrobial activities that ultimately resulted in eradication failure.     

Anatomy of an extensively drug-resistant Klebsiella pneumoniae outbreak in Tuscany,Italy

A protracted outbreak of New Delhi metallo-β-lactamase (NDM)–producing carbapenem-resistant Klebsiella pneumoniae started in Tuscany, Italy, in November 2018 and continued in 2020 and through 2021. To understand the regional emergence and transmission dynamics over time, we collected and sequenced the genomes of 117 extensively drug-resistant, NDM-producing K. pneumoniae isolates cultured over a 20-mo period from 76 patients at several healthcare facilities in southeast Tuscany. All isolates belonged to high-risk clone ST-147 and were typically nonsusceptible to all first-line antibiotics. Albeit sporadic, resistances to colistin, tigecycline, and fosfomycin were also observed as a result of repeated, independent mutations. Genomic analysis revealed that ST-147 isolates circulating in Tuscany were monophyletic and highly genetically related (including a network of 42 patients from the same hospital and sharing nearly identical isolates), and shared a recent ancestor with clinical isolates from the Middle East. While the bla_NDM-1 gene was carried by an IncFIB-type plasmid, our investigations revealed that the ST-147 lineage from Italy also acquired a hybrid IncFIB/IncHIB–type plasmid carrying the 16S methyltransferase armA gene as well as key virulence biomarkers often found in hypervirulent isolates. This plasmid shared extensive homologies with mosaic plasmids circulating globally including from ST-11 and ST-307 convergent lineages. Phenotypically, the carriage of this hybrid plasmid resulted in increased siderophore production but did not confer virulence to the level of an archetypical, hypervirulent K. pneumoniae in a subcutaneous model of infection with immunocompetent CD1 mice. Our findings highlight the importance of performing genomic surveillance to identify emerging threats.

Klebsiella pneumoniae is a leading cause of healthcare-associated infections including pneumonia, urinary tract, and bloodstream infections (1). Classical K. pneumoniae (cKp) frequently causes opportunistic infections in immunocompromised patients, the elderly, neonates, and patients with inserted medical devices (2). Of further concern, cKp strains can readily acquire antimicrobial resistances including extended-spectrum β-lactamases and carbapenemase-encoding genes (3). Prompting a major public health challenge, the global emergence and dissemination of multidrug-resistant K. pneumoniae (MDR-cKp) are attributed to a few successful clonal lineages, including newly identified “high-risk” sequence type (ST)-147 and ST-307 (4–6). Similar to ST-307, the MDR-cKp ST-147 lineage emerged in Europe during the mid-1990s, acquired plasmids encoding various carbapenemase genes (i.e., Verona Integron-Encoded metallo-β-lactamase [VIM] and New Delhi metallo-β-lactamase [NDM] as well as OXA-48 serine-carbapenemase variants) in the mid-2000s, and has now spread to all continents (4).In recent years, a distinct hypervirulent pathotype (hvKp) has been identified, and is recognized clinically by invasive and disseminated infections, in otherwise healthy individuals, that include meningitis, liver abscesses, and endophthalmitis (2). However, the defining features of hypervirulence remain ambiguous. Phenotypically, hvKp isolates have been characterized primarily by their hypermucoviscosity, antimicrobial susceptibility, and greater production of siderophores. Genetically, several virulence genes, carried on large virulence plasmids and integrative conjugative elements (ICEs), encoding for the biosynthesis of siderophores (aerobactin [iuc], salmochelin [iro], and yersiniabactin [ybt]), the modulation of mucoviscosity and capsule synthesis (rmpADC/rmpA2), metabolite transporter peg-344, and the production of genotoxic polyketide colibactin (clb) have been linked to the hvKp pathotype (5, 7, 8).Compounding the problem, convergent K. pneumoniae lineages with both virulence and resistance genes have been observed, albeit infrequently (3, 9, 10). Genotypic convergence most frequently occurs when MDR-cKp lineages acquire mobile genetic elements that carry the aforementioned virulence biomarker genes (11). Alarmingly, large hybrid plasmids that harbor both antimicrobial resistance and virulence genes have recently been reported in MDR isolates from multiple countries (6, 12–16). This includes sporadic instances of convergent bla_NDM-carrying ST-147 isolates detected in the United Kingdom in 2018 and 2019 (13, 14). Yet, in most cases, the clinical impact and the resulting virulence potential of convergent lineages is not well-understood.In this report, we investigated the emergence, genotypic convergence, phenotypic virulence, as well as the regional and nosocomial spread of an NDM-producing ST-147 clone causing an outbreak in Tuscany, Italy (17). This outbreak caused by an extensively drug-resistant (XDR) K. pneumoniae was first identified in November 2018 in the Tuscany region, where a significant increase in reported cases from seven hospitals led to expanded surveillance practices (18, 19). Recent surveillance data (20) suggest that, at the time of writing, this outbreak is ongoing with the risk of further transmission within and beyond Italy.     

From the Cover: The evolution of parasitism from mutualism in wasps pollinating the fig,Ficus microcarpa,in Yunnan Province,China

Theory identifies factors that can undermine the evolutionary stability of mutualisms. However, theory’s relevance to mutualism stability in nature is controversial. Detailed comparative studies of parasitic species that are embedded within otherwise mutualistic taxa (e.g., fig pollinator wasps) can identify factors that potentially promote or undermine mutualism stability. We describe results from behavioral, morphological, phylogenetic, and experimental studies of two functionally distinct, but closely related, Eupristina wasp species associated with the monoecious host fig, Ficus microcarpa, in Yunnan Province, China. One (Eupristina verticillata) is a competent pollinator exhibiting morphologies and behaviors consistent with observed seed production. The other (Eupristina sp.) lacks these traits, and dramatically reduces both female and male reproductive success of its host. Furthermore, observations and experiments indicate that individuals of this parasitic species exhibit greater relative fitness than the pollinators, in both indirect competition (individual wasps in separate fig inflorescences) and direct competition (wasps of both species within the same fig). Moreover, phylogenetic analyses suggest that these two Eupristina species are sister taxa. By the strictest definition, the nonpollinating species represents a “cheater” that has descended from a beneficial pollinating mutualist. In sharp contrast to all 15 existing studies of actively pollinated figs and their wasps, the local F. microcarpa exhibit no evidence for host sanctions that effectively reduce the relative fitness of wasps that do not pollinate. We suggest that the lack of sanctions in the local hosts promotes the loss of specialized morphologies and behaviors crucial for pollination and, thereby, the evolution of cheating.

Mutualisms are defined by the net benefits that are usually provided to individuals of each interacting species. These interactions often have influences far beyond the partner species directly interacting, and commonly provide many fundamental ecosystem services (1, 2). For example, in most cases, mycorrhizal fungi provide nutrients to forest trees, pollinators help flowering plants set fruit, intestinal bacteria promote nutrient uptake across diverse animal taxa, bacteria in lucinid clams help detoxify benthic sediments, and photosynthetic algae help maintain the coral reefs that structure nearshore marine environments around the world (3–6).However, while both partners in a mutualism usually receive net benefits from the interaction, mutualisms also usually impose costs on one or both partners interacting mutualistically. In the absence of fitness-aligning mechanisms between the partners (e.g., vertical transmission of symbionts, or repeated interactions with immediate fitness benefits), theory suggests that other mechanisms are needed to maintain a mutualism’s stability. Specifically, it has been proposed that a mutualism’s long-term stability often depends on mechanisms that limit the invasion of “cheater” individuals into the populations of either partner species (2, 3, 7–14). Broadly, cheaters can be defined as individuals (or species) that do not provide a beneficial service to their partners. By not providing a potentially costly service to their partners, cheaters are thought to benefit themselves relative to “cooperating” individuals or species in the short term (12–14). Invasion by such cheaters potentially erodes the net benefits resulting from the interaction, and therefore can lead to a breakdown of the mutualism itself.Consistent with this viewpoint, data suggest that in many cases the hosts (the larger of the two partners in the mutualism) can effectively promote cooperation by selectively allocating more resources to those symbionts that provide them with greater benefits. For example, some legumes have been shown to selectively allocate more resources to nodules containing rhizobia that are better at providing fixed nitrogen (14–16). In other studies, some host plants allocate more carbon to strains of mycorrhizal fungi that provide their hosts with more phosphorus (17–19).However, other authors question the biological relevance of much of this experimental evidence to natural species interactions, the direction of cause and effect, and the actual costs for providing benefits. A central question is the degree to which evidence for cheaters, defined as receiving fitness benefits by not providing services (relative to a mutualist that does provide benefits), exist at all (12, 13, 20). Key empirical issues concern whether or not individuals with a cheating phenotype do, in fact, cheat (impose a reproductive cost on their partner, relative to a cooperating mutualist). In addition, are cheating individuals that fail to benefit their host at least as fit as cooperating (mutualistic) individuals that do? Does the host allocate relatively more resources to more beneficial partners (effectively expressing sanctions against cheaters relative to cooperators)? Ultimately, this becomes a set of specific empirical questions: What is the relative fitness of cooperators and cheaters that interact with the same partner (host)? And, does the host effectively sanction cheaters relative to cooperators, and if so, to what degree (21, 22)? At a fundamental level, the relative fitness of cheaters and cooperators is only measurable and relevant within the context of a given host’s responses to them (3, 21, 22).To resolve these questions, it is useful to study those mutualistic host–symbiont interactions in which it is straightforward to measure and experimentally manipulate both benefits and costs to each partner under natural conditions (22–32). Ideally, we should be able to comparatively assess experimental results across a diversity of host–symbiont mutualisms that differ in what theory suggests should be key metrics (e.g., strength of host sanctions, existence and relative abundance of cheaters, and so forth).The over 750 species of host figs (Ficus: Moraceae) and their obligately pollinating wasps (Agaonidae: Hymenoptera) provide such a range of both experimental and comparative options that can be exploited to address these questions (22–32) (SI Appendix, Supplementary Text and Fig. S1). Ovipositing female fig wasps deposit a drop of fluid from their poison sac into the ovules of flowers into which they lay their eggs. This fluid initiates the formation of gall tissue upon which the developing larvae feed (33) (SI Appendix). At any given site, each fig species is typically pollinated by only one or two fig wasp species (24, 26). Morphological and molecular studies broadly support coevolution between genera of pollinating wasps and their respective sections of figs, while functional studies demonstrate coadaptation between them (33–51).For example, different groups of figs are characterized by either active or passive pollination (43–45) (SI Appendix). Passive pollination does not require specialized wasp morphologies or behaviors. In contrast, active pollination requires specialized female wasp morphologies and behaviors (44). The wasps collect pollen in their natal fig using coxal combs on their forelegs and store it in pollen pockets on their thoraxes (Fig. 1). After emerging from their natal figs, female wasps use volatile chemical scent cues produced by receptive figs to identify them (35–37). Dispersal flights from the natal fig are aided by prevailing winds and routinely cover scores of kilometers (38–41). Upon finding and entering a receptive fig of an appropriate host species, the foundress wasps repeatedly remove a few grains of pollen from their pockets and place them on the stigmatic surfaces of the individual flowers on which they attempt to lay eggs. Active pollination provides clear benefits for the host fig. Pollination is more efficient in actively pollinated fig species relative to passively pollinated species. This is reflected in the dramatically lower (∼1/10) amounts of pollen that active species typically produce (43–45). Conversely, active pollination appears to be costly for the wasps in terms of specialized body structures, energy, and time (22, 42, 45).Open in a separate windowFig. 1.Receptive F. microcarpa fig and pollinating structures of E. verticillata compared with Eupristina sp. (A) A cheater wasp (Eupristina sp.) laying eggs in a receptive fig of her host F. microcarpa. Pollinator wasps (E. verticillata) (B and C) have specialized morphological structures such as pollen pockets (black arrow) on the underside of their thorax and coxal combs on their forelegs (white arrows) that facilitate pollination. Pollen is stored in the pockets and coxal combs facilitate pollen transfer (43, 44). Cheater wasps (Eupristina sp.) (D and E) retain pollen pockets (black arrow) but lack coxal combs (white arrow).The most basic mutualistic services (e.g., the wasp’s ability to pollinate) can be experimentally manipulated. By allowing or restricting the female pollinator wasps’ access to, and ability to actively collect pollen, pollinators that either do (P+) or do not (P−) carry pollen can be produced and then introduced into receptive figs (22). Furthermore, the effects on pollinator wasp fitness (i.e., lifetime reproductive success) of pollinating the host fig (or not) can be quantified by counting their relative number of offspring in naturally occurring figs (22–32). Moreover, the many existing experimental studies using the same methodologies provide context for the findings of any given experiment (22–32). In previous experiments on actively pollinated fig species, wasps that do not pollinate (P−) have lower fitness than wasps that pollinate (P+) due to increased rates of fig abortion (killing all wasp larvae) and increased larval mortality reducing the number of P− offspring that emerge. These “host sanctions” are likely caused by selective resource allocation by the tree to better-pollinated figs (28). Although pollination typically leads to a higher number of wasp offspring, pollination is not an absolute requirement for wasp offspring to develop (28). Finally, there are at least two known cases of cheating wasp species, in which species of wasps that lack both morphologies and behaviors that permit efficient, active pollination of their host co-occur with a congeneric pollinator possessing these traits. Importantly, the species that lack these traits have clearly evolved within lineages of wasps that otherwise possess these apparently costly traits that permit them to actively pollinate their host (52, 53) (SI Appendix).Here, we exploit the opportunity provided by a third case (54, 55), in which a mutualistic active pollinator and a congeneric cheater species co-occur on the same monoecious host fig. Specifically, we conducted a combination of behavioral, morphological, phylogenetic, and experimental studies to compare these wasps and the outcomes of their interactions with their shared host fig, Ficus microcarpa (subgenus Urostigma: section Urostigma: subsection Conosycea), in and near the Xishuangbanna Tropical Botanical Garden (XTBG), China. Eupristina verticillata is the described active pollinator of F. microcarpa at this location, while an undescribed coexisting wasp species (Eupristina sp.) lacks the necessary adaptation for active pollination and appears to be a cheater (54, 55).In this study, we address and answer the following questions: 1) Does the undescribed Eupristina sp. wasp associated with F. microcarpa impose a reproductive cost on its host? We find that it does, and that the cost for host reproductive success is large. 2) Does the cheater exhibit significantly higher levels of reproductive success than the pollinator in their host? Yes, in both direct and indirect competition. Combined with the reproductive loss it imposes on the host, this species meets the strictest definition of cheater. 3) Is this cheater closely related (possibly a sister species) to the mutualist pollinator of their shared host? We find that within the context of other sympatric Eupristina species associated with seven fig hosts in this area, it is. Furthermore, it represents an independent loss of pollination structures from another case previously reported in this genus. 4) Does the host (F. microcarpa) locally exhibit detectable host sanctions against wasps that do not pollinate it? In sharp contrast with all 15 other cases of actively pollinated Ficus species that have been reported (22, 29–32), we find that it does not. 5) Given that cheaters exhibit equal or greater fitness than the pollinator, how do they coexist? Although deserving further study, we suggest that regular seasonal fluctuations in the relative abundances of the two wasp species facilitate their coexistence at this site (54, 55). Seasonal changes in the prevalence of westerly winds cause regional spatial heterogeneity in source pools of pollinators and cheaters that immigrate to the local host, F. microcarpa.     

SARS-CoV-2 evolution in animals suggests mechanisms for rapid variant selection

SARS-CoV-2 spillback from humans into domestic and wild animals has been well documented, and an accumulating number of studies illustrate that human-to-animal transmission is widespread in cats, mink, deer, and other species. Experimental inoculations of cats, mink, and ferrets have perpetuated transmission cycles. We sequenced full genomes of Vero cell–expanded SARS-CoV-2 inoculum and viruses recovered from cats (n = 6), dogs (n = 3), hamsters (n = 3), and a ferret (n = 1) following experimental exposure. Five nonsynonymous changes relative to the USA-WA1/2020 prototype strain were near fixation in the stock used for inoculation but had reverted to wild-type sequences at these sites in dogs, cats, and hamsters within 1- to 3-d postexposure. A total of 14 emergent variants (six in nonstructural genes, six in spike, and one each in orf8 and nucleocapsid) were detected in viruses recovered from animals. This included substitutions in spike residues H69, N501, and D614, which also vary in human lineages of concern. Even though a live virus was not cultured from dogs, substitutions in replicase genes were detected in amplified sequences. The rapid selection of SARS-CoV-2 variants in vitro and in vivo reveals residues with functional significance during host switching. These observations also illustrate the potential for spillback from animal hosts to accelerate the evolution of new viral lineages, findings of particular concern for dogs and cats living in households with COVID-19 patients. More generally, this glimpse into viral host switching reveals the unrealized rapidity and plasticity of viral evolution in experimental animal model systems.

Cross-species transmission events, which challenge pathogens to survive in new host environments, typically result in species-specific adaptations (1). These evolutionary changes can determine the pathogenicity and transmissibility of the virus in novel host species (2). Pathogen host switching resulting in epidemic disease is a rare event that is constrained by the interaction between species (3). In contrast to most species, humans move globally and regularly come into contact with domestic and peridomestic animals. Thus, when a novel virus spreads through human populations, there is an incidental risk of exposure to potentially susceptible nonhuman species.This scenario has become evident with the SARS-CoV-2 pandemic (SI Appendix, Table S1). Originally resulting from viral spillover into humans (4, 5), likely from an animal reservoir, spillback into a wide range of companion and wild animals has occurred or been shown to be plausible (6–10), and an increasing number of studies have indicated a high frequency of human-to-animal SARS-CoV-2 spillback transmission (11–18). Given the short duration of viral shedding, serologic analyses present a more accurate characterization of actual animal exposures to SARS-CoV-2. Such studies conducted in a variety of animal species have illustrated surprisingly high levels of seroconversion in cats and dogs and more recently free-ranging deer (SI Appendix, Table S1) (73–87). Other well-documented spillback events include numerous mink farms (SI Appendix, Table S1). In one of these reports, multiple feral cats living on a mink farm in the Netherlands during a SARS-CoV-2 outbreak were seropositive, likely from the direct transmission of the virus from mink to cats, as owned cats on the same farm were seronegative (19). This further illustrates that cross-species transmission chains are readily achieved. Recent surveys of free-ranging white-tailed deer in Illinois, Michigan, New York, and Pennsylvania revealed 33% seropositivity in free-ranging animals (20). Active SARS-CoV-2 infection was subsequently confirmed by PCR in a deer in Ohio (21). Together, these findings suggest the likely establishment of multiple domestic animal and wildlife reservoirs of SARS-CoV-2.The repeated interspecies transmission of a virus presents the potential for the acceleration of viral evolution and a possible source of novel strain emergence. This was demonstrated by reverse zoonosis of SARS-CoV-2 from humans to mink, followed by a selection in mink and zoonotic transmission back to humans (8). Given that reverse zoonosis has been reported repeatedly in dogs and cats from households where COVID-19 patients reside, and the fact that up to 50% of households worldwide are inhabited by these companion animals, there is potential for similar transmission chains to arise via humans and their pets (22, 23). Elucidating the viral selection and species-specific adaptation of SARS-CoV-2 in common companion animals is therefore of high interest. Furthermore, understanding viral evolutionary patterns in both companion animals and experimental animal models provides a valuable appraisal of species-specific viral variants that spotlight genomic regions for host–virus interaction.Significant attention has been directed at substrains evolving from the initial SARS-CoV-2 isolate (24), and an accumulating number of variant lineages have demonstrated increased transmission potential in humans (25, 26). The role, if any, that reverse zoonotic infections of nonhuman species and spillback may have played in the emergence of these novel variants of SARS-CoV-2 remains unknown. Documenting viral evolution following the spillover of SARS-COV-2 into new species is difficult given the unpredictability of timing of these events; therefore, experimental studies can greatly aid the understanding of SARS-CoV-2 evolution in animal species. Laboratory-based studies also provide the opportunity to determine how changes that occur during viral expansion in cell culture may influence in vivo infections. This information is highly relevant for the interpretation of in vivo and in vitro experiments using inoculum propagated in culture.We therefore assessed the evolution of SARS-CoV-2 during the three rounds of expansion of strain USA-WA1/2020 in Vero E6 cells (27), followed by measuring the variant emergence occurring during primary experimental infection in four mammalian hosts. Specifically, we compared variant proportions, insertions, and deletions occurring in genomes of SARS-CoV-2 recovered from dogs (n = 3), cats (n = 6), hamsters (n = 3), and a ferret (n = 1).     

Negative effects of nitrogen override positive effects of phosphorus on grassland legumes worldwide

Anthropogenic nutrient enrichment is driving global biodiversity decline and modifying ecosystem functions. Theory suggests that plant functional types that fix atmospheric nitrogen have a competitive advantage in nitrogen-poor soils, but lose this advantage with increasing nitrogen supply. By contrast, the addition of phosphorus, potassium, and other nutrients may benefit such species in low-nutrient environments by enhancing their nitrogen-fixing capacity. We present a global-scale experiment confirming these predictions for nitrogen-fixing legumes (Fabaceae) across 45 grasslands on six continents. Nitrogen addition reduced legume cover, richness, and biomass, particularly in nitrogen-poor soils, while cover of non–nitrogen-fixing plants increased. The addition of phosphorous, potassium, and other nutrients enhanced legume abundance, but did not mitigate the negative effects of nitrogen addition. Increasing nitrogen supply thus has the potential to decrease the diversity and abundance of grassland legumes worldwide regardless of the availability of other nutrients, with consequences for biodiversity, food webs, ecosystem resilience, and genetic improvement of protein-rich agricultural plant species.

Anthropogenic enrichment of nitrogen (N), phosphorus (P), and other nutrients from fertilizers and fossil fuel combustion is transforming natural ecosystems worldwide (1–5), leading to increased terrestrial plant productivity (6, 7) and loss of biodiversity (8, 9). Resource competition theory proposes that the capacity of species to persist at low levels of a limiting resource is a key mechanism underpinning competitive success. Consequently, plant functional types with specialized nutrient acquisition strategies are expected to have a competitive advantage in nutrient-limited environments but also to be especially vulnerable to nutrient enrichment (10–13).Legumes (Fabaceae) are one of the largest families of flowering plants, contributing over 650 genera and 19,000 taxa to global plant diversity (14). This diversity is important for biodiversity conservation and for genetic improvement of protein-rich crops and forage species for sustainable livestock production (15–17). Furthermore, the ability to fix atmospheric N₂ is one of the most important plant functional traits for influencing ecosystem processes, conferring N-fixing legumes with a disproportionately important role in ecosystem functioning (18, 19). For example, litter produced by legumes is nitrogen-rich and more easily decomposed by soil microorganisms, leading to flow on effects to higher trophic levels, including increased complexity of food webs and resistance of soil biophysical and chemical properties to ecosystem disturbance (20). As the success of legumes often arises from this capacity for symbiotic fixation of atmospheric N₂ in N-limited environments (21, 22), atmospheric N-deposition and other pathways of anthropogenic N supply are expected to drastically reduce their competitive advantage in plant communities (1, 5, 11, 23). This is especially the case for obligate-N-fixers that cannot down-regulate N-fixation (24, 25) and hence at higher soil N are disadvantaged by the high energetic cost of N-fixation (26).While concerns about global nutrient enrichment are focused on impacts of N on biodiversity and ecosystem productivity (1, 2, 27), changes in P and potassium (K) cycles (3, 4) or altered concentrations of other nutrients, can also influence the abundance and diversity of legumes in accordance with resource competition theory (10–13). Owing to the physiological demands of N-fixation, N-fixing legumes often have higher requirements for P, K, and other nutrients [e.g., molybdenum (Mo), iron (Fe), and calcium (Ca)] than non–N-fixing plants (28–31), and increases in these nutrients can favor N-fixing over non–N-fixing species, particularly in nutrient poor soils (21, 22). However, added nutrients may have synergistic effects (6, 32), leading to uncertainties in the expected net effect of P addition on the abundance of N-fixing legumes (26). For example, the phosphatases required for P acquisition from soils are rich in N; N addition may increase phosphatase investment, conferring legumes a superior phosphorus acquisition capacity in P- and N-limited environments (25, 29). Conversely, multiple nutrient addition is expected to allow nonlegumes to compete more effectively with legume species. Resulting light limitation may suppress legume growth and reduce the survival and establishment of new legume individuals (8, 9), especially of those legumes that are unable to reduce the costs of N fixation through down-regulation (10, 11, 15, 33–35).Despite these theoretical predictions, empirical evidence for the individual and interactive effects of changes in nutrient availability on legumes in natural ecosystems is limited (29, 36–39). Some experimental studies have shown decreased legume abundance with N addition and increased with P addition, but these studies are typically conducted at a single site and show both positive and negative interactive effects among nutrients (e.g., refs. 37, 40, and 41). Furthermore, minimal evidence is available regarding the influence of K or micronutrient enrichment on legume responses (29), and the underlying mechanisms of legume responses to nutrient addition, such as soil and climatic conditions, have not been investigated at global scales (but see ref. 26 for forest ecosystems).Using data from the Nutrient Network global collaborative experiment [https://nutnet.org/ (42)], we measured the cover, richness, and biomass responses of N-fixing legumes (hereafter legumes) to standardized experimental nutrient additions in 45 grasslands across six continents (SI Appendix, Fig. S1 and Table S1). Grasslands are a globally significant biome, covering more than one-third of the Earth’s ice-free land surface, accounting for a third of terrestrial net primary production (43), and supporting the livelihoods of more than 1.3 billion people. They are subject to chronic atmospheric nitrogen deposition due to fossil fuel combustion and are likely candidates for direct nitrogen fertilization (44). While N emissions in many regions of Europe have declined leading to plateaus or reductions in deposition (45), deposition in other world grasslands, such as the Mongolian Steppe, have increased in recent decades (e.g., ref. 46). Experimental sites included temperate and anthropic grasslands that spanned a broad range of geographical locations and ecological conditions, although were mostly from temperate latitudes (39) (SI Appendix, Table S1 and Fig. S1; see Methods for details).Three nutrients (N, P, K⁺) were applied in factorial combinations, resulting in eight treatments enabling evaluation of the interactive effects of N, P, and K addition (6, 8) on legumes. Over 3 to 6 y, 10 g⋅m⁻² N, P, and K were added annually to their respective treatment plots at the beginning of each site’s growing season; other nutrients in the K⁺ treatment [sulfur (S), magnesium (Mg), and micronutrients] were applied only in the first year to avoid toxicity (42). These nutrient levels were selected to ensure they were high enough to reduce nutrient limitation at a wide diversity of sites. They are at the higher end of the range for agricultural fertilizer application rates globally (5), and higher than atmospheric nutrient deposition rates (1, 3, 41, 43). In particular, our N-addition rate was about three times maximum current N-deposition rates in European grasslands and more generally across the globe (1, 47, 48).We used a standardized protocol (6, 42) to annually measure cover, richness, and biomass of legumes, forbs, and grasses in 1-m² permanent plots (Methods), starting in the year prior to the first nutrient application (Y_initial). Across all years and sites, we recorded 170 species of N-fixing grassland legumes, comprising 50 genera (SI Appendix, Table S2). The most species-rich genera were Trifolium (25 spp.), Astragalus (12 spp.), Vicia (11 spp.), and Lupinus (11 spp.). Vicia sativa, Trifolium repens, and Vicia hirsuta were the most frequent species across our sites (9.1%, 5.1%, and 4.9% of total occurrences, respectively). Each site contained one to eight legume species (Methods and SI Appendix, Table S1). Most legume species were perennials (∼60%), including 10 woody or shrub species (∼6% of species). On average, ∼3% and 4% of total live cover comprised annual and perennial legumes, respectively.We present results of nutrient addition for the third and the last available sampling year (years 3 to 6) after starting nutrient application in each site [noting sites started applying experimental treatments in different calendar years and ran for different lengths of time (SI Appendix, Table S1)]. To measure the relative impact of N, P, and K⁺ addition on legumes, we calculated the log ratio (LR) of legume abundance and richness in the third or last year in each plot versus the initial (pretreatment) value [LR = ln (Y_final/Y_initial)]. We used the pretreatment legume abundance in the LR instead of control plots (49) to control for initial legume abundance and spatial variability among plots (8, 50). We also calculated measures of legume colonization and extinction in each plot, and evaluated the effect of initial soil nutrient concentrations, community structure, and climatic conditions as contingencies for nutrient addition effects (see Methods for details). We analyzed the data using linear mixed-effects models (51–53), with nutrient treatments (i.e., N, P, K⁺, and their interactions) as fixed effects, and blocks nested within sites as random effects. Confidence intervals for model parameters were bootstrapped as a conservative method for hypothesis testing (51, 52) (see Methods for details).     

Global urban population exposure to extreme heat

Increased exposure to extreme heat from both climate change and the urban heat island effect—total urban warming—threatens the sustainability of rapidly growing urban settlements worldwide. Extreme heat exposure is highly unequal and severely impacts the urban poor. While previous studies have quantified global exposure to extreme heat, the lack of a globally accurate, fine-resolution temporal analysis of urban exposure crucially limits our ability to deploy adaptations. Here, we estimate daily urban population exposure to extreme heat for 13,115 urban settlements from 1983 to 2016. We harmonize global, fine-resolution (0.05°), daily temperature maxima and relative humidity estimates with geolocated and longitudinal global urban population data. We measure the average annual rate of increase in exposure (person-days/year⁻¹) at the global, regional, national, and municipality levels, separating the contribution to exposure trajectories from urban population growth versus total urban warming. Using a daily maximum wet bulb globe temperature threshold of 30 °C, global exposure increased nearly 200% from 1983 to 2016. Total urban warming elevated the annual increase in exposure by 52% compared to urban population growth alone. Exposure trajectories increased for 46% of urban settlements, which together in 2016 comprised 23% of the planet’s population (1.7 billion people). However, how total urban warming and population growth drove exposure trajectories is spatially heterogeneous. This study reinforces the importance of employing multiple extreme heat exposure metrics to identify local patterns and compare exposure trends across geographies. Our results suggest that previous research underestimates extreme heat exposure, highlighting the urgency for targeted adaptations and early warning systems to reduce harm from urban extreme heat exposure.

Increased exposure to extreme heat from both climate change (1–5) and the urban heat island (UHI) effect (6–9) threaten the sustainability of rapidly growing urban settlements worldwide. Exposure to dangerously high temperatures endangers urban health and development, driving reductions in labor productivity and economic output (10, 11) and increases in morbidity (1) and mortality (2, 3, 12). Within urban settlements, extreme heat exposure is highly unequal and most severely impacts the urban poor (13, 14). Despite the harmful and inequitable risks, we presently lack a globally comprehensive, fine-resolution understanding of where urban population growth intersects with increases in extreme heat (2, 6, 15). Without this knowledge, we have limited ability to tailor adaptations to reduce extreme heat exposure across the planet’s diverse urban settlements (6, 15, 16).Reducing the impacts of extreme heat exposure to urban populations requires globally consistent, accurate, and high-resolution measurement of both climate and demographic conditions that drive exposure (5, 15, 17). Such analysis provides decision makers with information to develop locally tailored interventions (7, 18, 19) and is also sufficiently broad in spatial coverage to transfer knowledge across urban geographies and climates (6). Information about exposures and interventions from diverse contexts is vital for the development of functional early warning systems (20) and can help guide risk assessments and inform future scenario planning (21). Existing global extreme heat exposure assessments (1, 2), however, do not meet these criteria (SI Appendix, Table S1) and are insufficient for decision makers. These studies are coarse grained (>0.5° spatial resolution), employ disparate or single metrics that do not capture the complexities of heat-health outcomes (22), do not separate urban from rural exposure (19), and rely on climate reanalysis products that can be substantially (∼1 to 3 °C) cooler than in situ data observations (5, 23, 24). In fact, widely cited benchmarks (25) that estimate extreme heat with the version 5 of the European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5) (26) may greatly underestimate total global exposure to extreme heat (5, 23, 24). Using a 40.6 °C daily maximum 2-m air temperature threshold (T_max), recent analysis found that ERA5 T_max drastically underestimated the number of extreme heat days per year compared to in situ observations (23). Finally, few studies (2, 18) have assessed urban extreme heat exposure across data-sparse (23) rapidly urbanizing regions, such as sub-Saharan Africa, the Middle East, and Southern Asia (27), that may be most impacted by increased extreme heat events due to climate change (3, 5, 28).Here, we present a globally comprehensive, fine-resolution, and longitudinal estimate of urban population exposure to extreme heat––referred to henceforth as exposure––for 13,115 urban settlements from 1983 to 2016. To accomplish this, we harmonize global, fine-grained (0.05° spatial resolution) T_max estimates (23) with global urban population and spatial extent data (29). For each urban settlement, we calculate area-averaged daily wet bulb globe temperature (WBGT_max) (30) and heat index (HI_max) (31) maxima using Climate Hazards Center InfraRed Temperature with Stations Daily (CHIRTS-daily) T_max (23) and down-scaled daily minimum relative humidity (RH_min) estimates (32). CHIRTS-daily is better suited to measure urban extreme heat exposure than other gridded temperature datasets used in recent global extreme heat studies (SI Appendix, Table S1) for two reasons. First, it is more accurate, especially at long distances (refer to figure 3 in ref. 23), than widely used gridded temperature datasets to estimate urban temperature signals worldwide (SI Appendix, Figs. S1 and S2). Second, it better captures the spatial heterogeneity of T_max across diverse urban contexts (SI Appendix, Fig. S3). These factors are key for measuring extreme heat exposure in rapidly urbanizing, data-sparse regions.As discussed in refs. 23 and 24, the number of in situ temperature observations is far too low across rapidly urbanizing (27) regions to resolve spatial and temporal urban extreme heat fluctuations, which can vary dramatically over small distances and time periods. For example, of the more than 3,000 urban settlements in India (29), only 111 have reliable station observations (SI Appendix, Fig. S3). While climate reanalyses can help overcome these limitations, they are coarse grained (SI Appendix, Table S1) and suffer from mean bias, and, to a lesser degree, temporal fidelity. ERA5 has been shown to substantially underestimate the increasing frequencies of heat extremes (figure 4 in ref. 23), while Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA2) fails to represent the substantial increase in recent monthly T_max values (figure 8 in ref. 24). These datasets dramatically underestimate increases in warming. CHIRTS-daily overcomes these limitations by coherently stacking information from a high-resolution (0.05°) climatology-derived surface emission temperature (24), interpolated in situ observations, and ERA5 reanalysis to produce a product that has been explicitly developed to monitor and assess temperature related hazards (23). As such, CHIRTS-daily is best suited to capture variation in exposure across urban settlements in rapidly urbanizing (27), data-sparse regions such as sub-Saharan Africa, the Middle East, and Southern Asia (SI Appendix, Fig. S3) (24).We measure exposure in person-days/year⁻¹—the number of days per year that exceed a heat exposure threshold multiplied by the total urban population exposed (5). We then estimate annual rates of increase in exposure at the global (Fig. 1), regional (SI Appendix, Table S2), national (SI Appendix, Table S3), and municipality levels from 1983 to 2016 (SI Appendix, Table S4). At each spatial scale, we separate the contribution to exposure trajectories from total urban warming and population growth (5). For clarity, total urban warming refers to the combined increase of extreme heat in urban settlements from both the UHI effect and anthropogenic climate change. We do not decouple these two forcing agents (33, 34). However, we identify which urban settlements have warmed the fastest by measuring the rate of increase in the number of days per year that exceed the two extreme heat thresholds described below (15). Our main findings use an extreme heat exposure threshold defined as WBGT_max > 30 °C, the International Standards Organization (ISO) occupational heat stress threshold for risk of heat-related illness among acclimated persons at low metabolic rates (100 to 115 W) (30). WBGT_max is a widely used heat stress metric (35) that captures the biophysical response (36) of hot temperature–humidity combinations (3, 17) that reduce labor output (36), lead to heat-related illness (36), and can cause death (23). In using a threshold WBGT_max > 30 °C, which has been associated with higher mortality rates among vulnerable populations (37), we aim to identify truly extremely hot temperature–humidity combinations (17) that can harm human health and well-being. We recognize, however, that strict exposure thresholds do not account for individual-level risks and vulnerabilities related to acclimatization, socio-economic, or health status or local infrastructure (18, 19, 38). We also note that there are a range of definitions of exposure, and we provide further analysis identifying 2-d or longer periods during which the maximum heat index (HI_max) (31) exceeded 40.6 °C (SI Appendix, Figs. S4–S6) following the US National Weather Service’s definition for an excessive heat warning (39).Open in a separate windowFig. 1.Global urban population exposure to extreme heat, defined by 1-d or longer periods when WBGT_max > 30 °C, from 1983 to 2016 (A), with the contribution from population growth (B), and total urban warming (C) decoupled.     

Regulation of beta-amyloid production in neurons by astrocyte-derived cholesterol

Alzheimer’s disease (AD) is characterized by the presence of amyloid β (Aβ) plaques, tau tangles, inflammation, and loss of cognitive function. Genetic variation in a cholesterol transport protein, apolipoprotein E (apoE), is the most common genetic risk factor for sporadic AD. In vitro evidence suggests that apoE links to Aβ production through nanoscale lipid compartments (lipid clusters), but its regulation in vivo is unclear. Here, we use superresolution imaging in the mouse brain to show that apoE utilizes astrocyte-derived cholesterol to specifically traffic neuronal amyloid precursor protein (APP) in and out of lipid clusters, where it interacts with β- and γ-secretases to generate Aβ-peptide. We find that the targeted deletion of astrocyte cholesterol synthesis robustly reduces amyloid and tau burden in a mouse model of AD. Treatment with cholesterol-free apoE or knockdown of cholesterol synthesis in astrocytes decreases cholesterol levels in cultured neurons and causes APP to traffic out of lipid clusters, where it interacts with α-secretase and gives rise to soluble APP-α (sAPP-α), a neuronal protective product of APP. Changes in cellular cholesterol have no effect on α-, β-, and γ-secretase trafficking, suggesting that the ratio of Aβ to sAPP-α is regulated by the trafficking of the substrate, not the enzymes. We conclude that cholesterol is kept low in neurons, which inhibits Aβ accumulation and enables the astrocyte regulation of Aβ accumulation by cholesterol signaling.

Alzheimer’s disease (AD), the most prevalent neurodegenerative disorder, is characterized by the progressive loss of cognitive function and the accumulation of amyloid β (Aβ) peptide and phosphorylated tau (1). Amyloid plaques are composed of aggregates of Aβ peptide, a small hydrophobic protein excised from the transmembrane domain of amyloid precursor protein (APP) by proteases known as beta- (β-) and gamma- (γ-) secretases (SI Appendix, Fig. S1A). In high concentrations, Aβ peptide can aggregate to form Aβ plaques (2–4). The nonamyloidogenic pathway involves a third enzyme, alpha- (α-) secretase, which generates a soluble APP fragment (sAPP-α), helps set neuronal excitability in healthy individuals (5), and does not contribute to the generation of amyloid plaques. Therefore, by preventing Aβ production, α-secretase–mediated APP cleavage reduces plaque formation. Strikingly, both pathways are finely regulated by cholesterol (6) (SI Appendix, Fig. S1B).In cellular membranes, cholesterol regulates the formation of lipid clusters (also known as lipid rafts) and the affinity of proteins to lipid clusters (7), including β-secretase and γ-secretase (8–10). α-secretase does not reside in lipid clusters; rather, α-secretase is thought to reside in a region made up of disordered polyunsaturated lipids (11). The location of APP is less clear. In detergent-resistant membrane (DRM) studies, it primarily associates with lipid from the disordered region, although not exclusively (8, 10, 12–14). Endocytosis is thought to bring APP in proximity to β-secretase and γ-secretase, and this correlates with Aβ production. Cross-linking of APP with β-secretase on the plasma membrane also increases Aβ production, leading to a hypothesis that lipid clustering in the membrane contributes to APP processing (11, 14, 15) (SI Appendix, Fig. S1A). Testing this hypothesis in vivo has been hampered by the small size and transient nature of lipid clusters (often <100 nm), which is below the resolution of light microscopy.Superresolution imaging has emerged as a complimentary technique to DRMs, with the potential to interrogate cluster affinity more directly in a native cellular environment (16). We recently employed superresolution imaging to establish a membrane-mediated mechanism of general anesthesia (17). In that mechanism, cholesterol causes lipid clusters to sequester an enzyme away from its substrate. Removal of cholesterol then releases and activates the enzyme by giving it access to its substrate (SI Appendix, Fig. S1C) (7, 18). A similar mechanism has been proposed to regulate the exposure of APP to its cutting enzymes (11, 15, 19–21).Neurons are believed to be the major source of Aβ in normal and AD brains (22, 23). In the adult brain, the ability of neurons to produce cholesterol is impaired (24). Instead, astrocytes make cholesterol and transport it to neurons with apolipoprotein E (apoE) (25–27). Interestingly, apoE, specifically the e4 subtype (apoE4), is the strongest genetic risk factor associated with sporadic AD (28, 29). This led to the theory that astrocytes may be controlling Aβ accumulation through regulation of the lipid cluster function (11, 15, 19), but this has not yet been shown in the brain of an animal. Here, we show that astrocyte-derived cholesterol controls Aβ accumulation in vivo and links apoE, Aβ, and plaque formation to a single molecular pathway.     

Emerging predictable features of replicated biological invasion fronts

Biological dispersal shapes species’ distribution and affects their coexistence. The spread of organisms governs the dynamics of invasive species, the spread of pathogens, and the shifts in species ranges due to climate or environmental change. Despite its relevance for fundamental ecological processes, however, replicated experimentation on biological dispersal is lacking, and current assessments point at inherent limitations to predictability, even in the simplest ecological settings. In contrast, we show, by replicated experimentation on the spread of the ciliate Tetrahymena sp. in linear landscapes, that information on local unconstrained movement and reproduction allows us to predict reliably the existence and speed of traveling waves of invasion at the macroscopic scale. Furthermore, a theoretical approach introducing demographic stochasticity in the Fisher–Kolmogorov framework of reaction–diffusion processes captures the observed fluctuations in range expansions. Therefore, predictability of the key features of biological dispersal overcomes the inherent biological stochasticity. Our results establish a causal link from the short-term individual level to the long-term, broad-scale population patterns and may be generalized, possibly providing a general predictive framework for biological invasions in natural environments.What is the source of variance in the spread rates of biological invasions? The search for processes that affect biological dispersal and sources of variability observed in ecological range expansions is fundamental to the study of invasive species dynamics (1–10), shifts in species ranges due to climate or environmental change (11–13), and, in general, the spatial distribution of species (3, 14–16). Dispersal is the key agent that brings favorable genotypes or highly competitive species into new ranges much faster than any other ecological or evolutionary process (1, 17). Understanding the potential and realized dispersal is thus key to ecology in general (18). When organisms’ spread occurs on the timescale of multiple generations, it is the byproduct of processes that take place at finer spatial and temporal scales that are the local movement and reproduction of individuals (5, 10). The main difficulty in causally understanding dispersal is thus to upscale processes that happen at the short-term individual level to long-term and broad-scale population patterns (5, 18–20). Furthermore, the large fluctuations observed in range expansions have been claimed to reflect an intrinsic lack of predictability of the phenomenon (21). Whether the variability observed in nature or in experimental ensembles might be accounted for by systematic differences between landscapes or by demographic stochasticity affecting basic vital rates of the organisms involved is an open research question (10, 18, 21, 22).Modeling of biological dispersal established the theoretical framework of reaction–diffusion processes (1–3, 23–25), which now finds common application in dispersal ecology (5, 14, 22, 26–30) and in other fields (17, 23, 25, 31–36). Reaction–diffusion models have also been applied to model human colonization processes (31), such as the Neolithic transition in Europe (25, 37, 38). The classical prediction of reaction–diffusion models (1, 2, 24, 25) is the propagation of an invading wavefront traveling undeformed at a constant speed (Fig. 1E). Such models have been widely adopted by ecologists to describe the spread of organisms in a variety of comparative studies (5, 10, 26) and to control the dynamics of invasive species (3, 4, 6). The extensive use of these models and the good fit to observational data favored their common endorsement as a paradigm for biological dispersal (6). However, current assessments (21) point at inherent limitations to the predictability of the phenomenon, due to its intrinsic stochasticity. Therefore, single realizations of a dispersal event (as those addressed in comparative studies) might deviate significantly from the mean of the process, making replicated experimentation necessary to allow hypothesis testing, identification of causal relationships, and to potentially falsify the models’ assumptions (39).Open in a separate windowFig. 1.Schematic representation of the experiment. (A) Linear landscape. (B) Individuals of the ciliate Tetrahymena sp. move and reproduce within the landscape. (C) Examples of reconstructed trajectories of individuals (Movie S1). (D) Individuals are introduced at one end of a linear landscape and are observed to reproduce and disperse within the landscape (not to scale). (E) Illustrative representation of density profiles along the landscape at subsequent times. A wavefront is argued to propagate undeformed at a constant speed v according to the Fisher–Kolmogorov equation.Here, we provide replicated and controlled experimental support to the theory of reaction–diffusion processes for modeling biological dispersal (23–25) in a generalized context that reproduces the observed fluctuations. Firstly, we experimentally substantiate the Fisher–Kolmogorov prediction (1, 2) on the existence and the mean speed of traveling wavefronts by measuring the individual components of the process. Secondly, we manipulate the inclusion of demographic stochasticity in the model to reproduce the observed variability in range expansions. We move from the Fisher–Kolmogorov equation (Materials and Methods) to describe the spread of organisms in a linear landscape (1, 2, 24, 25). The equation couples a logistic term describing the reproduction of individuals with growth rate r and carrying capacity K and a diffusion term accounting for local movement, epitomized by the diffusion coefficient D . These species’ traits define the characteristic scales of the dispersal process. In this framework, a population initially located at one end of a linear landscape is predicted to form a wavefront of colonization invading empty space at a constant speed (1, 2, 24, 25), which we measured in our dispersal experiment (Fig. 1D and SI Text).     

Oxidative regulation of chloroplast enzymes by thioredoxin and thioredoxin-like proteins in Arabidopsis thaliana

Thioredoxin (Trx) is a protein that mediates the reducing power transfer from the photosynthetic electron transport system to target enzymes in chloroplasts and regulates their activities. Redox regulation governed by Trx is a system that is central to the adaptation of various chloroplast functions to the ever-changing light environment. However, the factors involved in the opposite reaction (i.e., the oxidation of various enzymes) have yet to be revealed. Recently, it has been suggested that Trx and Trx-like proteins could oxidize Trx-targeted proteins in vitro. To elucidate the in vivo function of these proteins as oxidation factors, we generated mutant plant lines deficient in Trx or Trx-like proteins and studied how the proteins are involved in oxidative regulation in chloroplasts. We found that f-type Trx and two types of Trx-like proteins, Trx-like 2 and atypical Cys His-rich Trx (ACHT), seemed to serve as oxidation factors for Trx-targeted proteins, such as fructose-1,6-bisphosphatase, Rubisco activase, and the γ-subunit of ATP synthase. In addition, ACHT was found to be involved in regulating nonphotochemical quenching, which is the mechanism underlying the thermal dissipation of excess light energy. Overall, these results indicate that Trx and Trx-like proteins regulate chloroplast functions in concert by controlling the redox state of various photosynthesis-related proteins in vivo.

Plant chloroplasts have evolved multiple strategies with which to adapt photosynthesis to fluctuating light environments. One such strategy involves the redox regulation of various enzymes that function in photosynthesis reactions. Multiple photosynthesis-related proteins, such as the four Calvin–Benson cycle enzymes (glyceraldehyde-3-phosphate dehydrogenase, fructose-1,6-bisphosphatase [FBPase], sedoheptulose-1,7-bisphosphatase [SBPase], and phosphoribulokinase [PRK]), possess redox-active Cys residues (1, 2). In addition, the γ-subunit of ATP synthase (CF₁-γ) and two regulatory proteins associated with Calvin–Benson cycle enzymes, CP12 and ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) activase (RCA), are also redox-regulated (2–4). In the 1970s thioredoxin (Trx) was identified as a reducing power mediator for FBPase and SBPase in chloroplasts (5, 6). In a light-containing environment, reducing power is transferred from the photosynthetic electron transport system to Trx via ferredoxin and ferredoxin-Trx reductase (6). Trx then achieves light-dependent activation of its target enzymes by reducing the disulfide bond on these enzymes.In chloroplasts, NADPH-Trx reductase C (NTRC) works in parallel with the Trx-dependent system as another redox pathway. NTRC is also a redox-responsive protein containing both NADPH-dependent Trx reductase and Trx domains; these enable NTRC to reduce its target proteins using the reducing power of NADPH (7). NTRC can reduce 2-Cys peroxiredoxin (2-Cys Prx) in addition to several Trx-targeted proteins (8–12). 2-Cys Prx utilizes reducing power to reduce reactive oxygen species such as H₂O₂ (13). In chloroplasts, NTRC is thought to be a major electron donor for 2-Cys Prx (14) because the reducing power transfer efficiency from NTRC is extremely high compared with that from typical chloroplast Trx proteins (12). Plants deficient in NTRC show severe phenotypes, such as stunted growth, low chlorophyll content, and very high nonphotochemical quenching (NPQ) (7, 11, 12, 14–17). Thus, it is clear that NTRC plays important physiological roles in chloroplasts.Redox-regulated proteins in the stroma are reduced in the light and then reoxidized in the dark (18, 19). Reoxidation is an important process in plants; for example, we recently showed that the reoxidation of chloroplast NADP-malate dehydrogenase is important for maintaining NADPH homeostasis in chloroplasts, particularly in an environment with fluctuating light (20). Despite the importance of the oxidation process, the proteins involved in target oxidation have yet to be clarified. Recently, Trx-like proteins, such as Trx-like 2 (TrxL2) and atypical Cys His-rich Trx (ACHT), have been suggested as oxidation factors (21–27). These reports were mainly based on the results of in vitro experiments, suggesting that Trx-like proteins transfer the reducing power of Trx-targeted proteins to H₂O₂ via 2-Cys Prx. However, the functions of these proteins in vivo are not known very well. The so-called common Trxs belonging to f-, m-, x-, y- (or z-?) types were also thought to be the candidate of the oxidation factor. Because it is known that, particularly, Trx-f can oxidize its target proteins under certain conditions in vitro (25, 28), we focused this work on Trx-f.Target oxidation by ACHT1 and ACHT2, among five ACHT isoforms in Arabidopsis thaliana (29), has been demonstrated in vitro (25). ACHT1 and ACHT2 are broadly conserved in photosynthetic organisms, including green algae, moss, and seed plants (30). Their amino acid sequences and biochemical properties are similar (SI Appendix, Fig. S1A) (25, 29). In addition, ACHT1 and ACHT2 (designated also as Lilium5 and Lilium2, respectively) are predicted to originate from the same ancestral gene (31). Comparison of the expression patterns of ACHT1 and ACHT2 in the database shows that ACHT2 is expressed more than ACHT1, especially in leaves (SI Appendix, Fig. S1B) (32), suggesting that ACHT2 may play a dominant role in A. thaliana leaves.Oxidation of target proteins by the TrxL2 isoforms from A. thaliana, namely TrxL2.1 and TrxL2.2, has been demonstrated in vitro (22). TrxL2 genes are also conserved in photosynthetic organisms, such as seed plants, moss, and some green algae, but not in Chlamydomonas reinhardtii (30). Although the amino acid sequences and biochemical properties of TrxL2.1 and TrxL2.2 are similar (SI Appendix, Fig. S2A) (22), their expression patterns are different, and TrxL2.1 is reported to be more expressed than TrxL2.2, particularly in leaves (SI Appendix, Fig. S2B) (32). In addition, TrxL2.1 expression seems to be regulated by the circadian rhythm and the rhythm of temperature change (SI Appendix, Fig. S2C). The expression of TrxL2.1 is more strongly induced before and during light-to-dark transitions than TrxL2.2, suggesting that TrxL2.1 plays a predominant role during these periods.In the present study, we generated A. thaliana mutant plant lines deficient in Trx-f1 and Trx-f2, TrxL2.1, or ACHT1 and ACHT2, whose target oxidation activities are well studied in vitro, and used these plants to investigate redox state changes in chloroplasts. We found that Trx-f, TrxL2.1, ACHT1, and ACHT2 are involved in the oxidation of FBPase, CF₁-γ, and RCA. ACHT2 also seemed to be involved in the regulation of NPQ. Furthermore, the knockout of Trx-like proteins suppressed the impact of NTRC deficiency in plants, suggesting that a connection existed between the NTRC system and Trx-like protein-involving system.     

Selective treatment and monitoring of disseminated cancer micrometastases in vivo using dual-function,activatable immunoconjugates

Drug-resistant micrometastases that escape standard therapies often go undetected until the emergence of lethal recurrent disease. Here, we show that it is possible to treat microscopic tumors selectively using an activatable immunoconjugate. The immunoconjugate is composed of self-quenching, near-infrared chromophores loaded onto a cancer cell-targeting antibody. Chromophore phototoxicity and fluorescence are activated by lysosomal proteolysis, and light, after cancer cell internalization, enabling tumor-confined photocytotoxicity and resolution of individual micrometastases. This unique approach not only introduces a therapeutic strategy to help destroy residual drug-resistant cells but also provides a sensitive imaging method to monitor micrometastatic disease in common sites of recurrence. Using fluorescence microendoscopy to monitor immunoconjugate activation and micrometastatic disease, we demonstrate these concepts of “tumor-targeted, activatable photoimmunotherapy” in a mouse model of peritoneal carcinomatosis. By introducing targeted activation to enhance tumor selectively in complex anatomical sites, this study offers prospects for catching early recurrent micrometastases and for treating occult disease.Metastatic disease remains the main cause of cancer-related death despite advances in cytoreductive surgery and chemotherapy (1–4). An ongoing dilemma is the lack of options to address residual micrometastases that escape standard treatments and detection by current imaging technologies (3). In addition to spread via hematogenous and lymphatic routes (5), diffuse micrometastatic spread throughout anatomical cavities is also problematic, including peritoneal dissemination resulting from cancers of the colon (6), pancreas (7), and ovary (1, 2, 4). These obstacles are pronounced in the treatment of epithelial ovarian cancer (EOC), a prime example of a frequently recurrent disease characterized by residual micrometastases. Due to the lack of screening methods or distinct symptoms during early progression, the vast majority of EOC cases are diagnosed once the disease has metastasized and formed numerous nodules studding the peritoneal cavity (1, 2, 4). Although a significant fraction of patients (∼35%) appear to achieve a complete response after cytoreductive surgery and follow-up chemotherapy, a small number of cells with intrinsic or acquired resistance are responsible for recurrence and poor survival (1, 2, 4, 8). These residual micrometastases are clinically occult until gross recurrence, which is often refractory to standard treatments (1, 2, 4). Laparotomy, an invasive surgical reassessment, frequently fails to detect residual disease (9) while noninvasive clinical imaging modalities also have poor sensitivity for subcentimeter tumors (10, 11).To address the challenges associated with treating and detecting occult, residual, and drug-resistant micrometastases before gross recurrence, it is necessary to develop (i) targeted treatments with high tumor selectivity and distinct mechanisms of cell death (12–14) to overcome dose-limiting toxicities and chemoresistance; and (ii) high-resolution approaches with sufficient contrast to monitor microscopic disease. Here, we address both of these needs by developing an activatable construct targeted to markers overexpressed by cancer cells with dual functionality for both therapy and imaging, and integrate this into a quantitative fluorescence microendoscopy platform for longitudinal monitoring of micrometastases. This approach realizes treatment selectivity and imaging fidelity at the microscale.Targeted agents carrying “always-on,” unquenched chromophores have emerged for targeted therapy and imaging at the macroscale. In a promising clinical study, intraoperative visualization of EOC nodules labeled with a targeted, always-on fluorescent probe facilitated the identification of more tumor deposits by surgeons compared with conventional bright-field illumination (15). This development may ultimately translate to fluorescence-guided resection for more radical cytoreductive surgery, leaving less disease behind (15–17). Photoimmunotherapy (PIT) using always-on immunoconjugates is a targeted form of photodynamic therapy—first reported in the seminal works of Levy and colleagues (18)—that has been shown to hold promise by us (19–23) and by others (18, 24, 25). Because photodynamic agents are mechanistically distinct from traditional treatment modalities (13, 14), are effective against radioresistant and chemoresistant cells (19, 20, 26), and can also resensitize resistant cells to chemotherapy (20, 23), the development of PIT is of importance for overcoming drug resistance. In fact, photodynamic therapy has been used in the treatment of disseminated peritoneal disease with some success intraoperatively (27) and endoscopically in the lung, bladder, and esophagus (SI Text, Note S1).Integrating the concepts of targeted therapy and imaging, a recent proof-of-concept study performed dual epidermal growth factor receptor (EGFR)-targeted PIT and imaging of localized, macroscopic tumors using always-on immunoconjugates (25). This study used a mouse model derived from s.c. implantation of A431 squamous-cell carcinoma cells that express abnormally high levels of EGFR (25). A limitation of PIT is persistent phototoxicity and background signal in nontarget tissues due to unbound and circulating always-on immunoconjugates, which compromise treatment and imaging selectivity at the microscale. It therefore remains uncertain whether PIT is safe and effective for treatment of micrometastases—the ultimate test of treatment selectivity. It is also unknown whether always-on immunoconjugates have sufficient tumor selectivity for treatment and imaging of tumors that express more realistic levels of the target molecule. Given these limitations, we sought to develop a more selective type of PIT—termed tumor-targeted, activatable PIT (taPIT)—and tumor imaging based on dual-function immunoconjugates that enable activatable, near-infrared (NIR)-mediated PIT as well as activatable fluorescence imaging (Fig. 1). This approach—building on the concept of lysosome-activated imaging probes suggested by Achilefu, Urano, Kobayashi, and coworkers (28, 29)—not only achieves greater treatment selectivity than always-on PIT but also enables resolution of microscopic tumor deposits.Open in a separate windowFig. 1.Concepts of tumor-targeted, activatable photoimmunotherapy (taPIT) and longitudinal monitoring of micrometastases in vivo. (A) Cet-BPD—a dual-function, activatable immunoconjugate for both taPIT and monitoring of micrometastases—consists of multiple BPD molecules conjugated to each cetuximab molecule. The BPD molecules remain self-quenched until EGFR binding and cellular internalization. (B) Schematic of Cet-BPD intracellular activation. (C) taPIT enables tumor-confined phototoxicity, whereas always-on agents and immunoconjugates result in nonspecific damage to normal tissues. (D) Mouse model of micrometastatic epithelial ovarian cancer (EOC) and fluorescence microendoscopy schematics. (E) (Left) In vivo fluorescence microendoscopy of control no-tumor and EOC mice on days 5 and 14 posttumor inoculation. (Right) Corresponding ex vivo immunofluorescence images show human EOC and mouse endothelial cells (ECs) stained with anti-CK8 and -CD31 antibodies, respectively. (Scale bars: 100 μm.) Note that all images in this report are displayed on a linear scale deliberately without saturation. Nonlinear, saturated image display appears to show higher contrast, but such a representation is not quantitative (Fig. S1). (F) Schematic of i.p. Cet-BPD photoactivation using a diffusing tip fiber and scattering media to enable efficient, targeted wide-field treatment of micrometastatic disease spread throughout the abdominal cavity by stepwise irradiation of each quadrant within the cavity.Here, we demonstrate these concepts of dual-function, tumor-targeted activatable immunoconjugates for selective treatment and quantitative, longitudinal imaging of micrometastases in vivo using a clinically motivated model of advanced-stage ovarian carcinomatosis (30). In this model, peritoneal micrometastases are derived from human EOC cells (OVCAR5) that possess intrinsic resistance to chemotherapy (8, 31). Using activatable immunoconjugates, a custom-built microendoscope (32) and a newly developed image analysis workflow (Figs. S2 and S3), we present minimally invasive, quantitative, and repeated measurements of micrometastases during therapy. Using fluorescence microendoscopy to characterize immunoconjugate pharmacokinetics and to monitor micrometastatic burden reduction in vivo, we demonstrate tumor-selective immunoconjugate activation and taPIT efficacy. This targeted activation significantly reduces nonspecific phototoxicity and fluorescence to provide therapeutic response monitoring of microscopic tumor nodules in a complex model of disseminated disease.     

From the Cover: Sea surface height evidence for long-term warming effects of tropical cyclones on the ocean

Tropical cyclones have been hypothesized to influence climate by pumping heat into the ocean, but a direct measure of this warming effect is still lacking. We quantified cyclone-induced ocean warming by directly monitoring the thermal expansion of water in the wake of cyclones, using satellite-based sea surface height data that provide a unique way of tracking the changes in ocean heat content on seasonal and longer timescales. We find that the long-term effect of cyclones is to warm the ocean at a rate of 0.32 ± 0.15 PW between 1993 and 2009, i.e., ∼23 times more efficiently per unit area than the background equatorial warming, making cyclones potentially important modulators of the climate by affecting heat transport in the ocean–atmosphere system. Furthermore, our analysis reveals that the rate of warming increases with cyclone intensity. This, together with a predicted shift in the distribution of cyclones toward higher intensities as climate warms, suggests the ocean will get even warmer, possibly leading to a positive feedback.Strong winds associated with tropical cyclones (TCs) increase air–sea heat fluxes, favoring the intensification of storms, and generate vigorous vertical mixing in the upper ocean, stirring warm surface waters with colder waters below (1–6). The wake produced by the passage of TCs is thus characterized by a surface cold anomaly and a subsurface warm anomaly (1–3, 6, 7). After the TC passage, the sea surface cold anomaly dissipates quickly (8–10), due in part to anomalous air–sea heat fluxes (9, 11), whereas the subsurface warm anomaly is believed to persist over a much longer period (12). This has led to the suggestion that the net long-term effect of TCs is to pump heat into the ocean (13–16). Such a flux of heat into the low-latitude ocean has been proposed to be an important modulator of local and remote climate (12, 17–22).During the past decade or so, several studies have been devoted to estimating the magnitude of this heating effect, using sea surface temperature (SST) data (13–16). However, owing to a lack of subsurface temperature observations, these studies relied upon many assumptions that led to large and poorly quantified uncertainties (SI Appendix, SI Results). Furthermore, it is currently highly debated how much (if any) of the estimated warming survives beyond winter season when the deepening of the mixed layer cools the upper ocean. To avoid the ideological and methodological challenges inherent in the previous work, we take a more straightforward approach that was first proposed by Emanuel (13, 23) and quantify the TC-induced warming effect on the ocean by estimating the thermal expansion of water in the wake of Northern Hemisphere TCs, using satellite-derived sea surface height (SSH) data (24) together with tropical cyclone best-track data (25, 26). Combining these two datasets allows us to track the SSH anomalies (SSHAs) around the TC-generated wake beyond the winter season and thus provides a clear picture of the temporal evolution of the TC-induced changes in the ocean heat content. Details on the data and methods are given in SI Appendix, SI Data and Methods.     

Cosmogenic nuclide dating of Australopithecus at Sterkfontein,South Africa

Sterkfontein is the most prolific single source of Australopithecus fossils, the vast majority of which were recovered from Member 4, a cave breccia now exposed by erosion and weathering at the landscape surface. A few other Australopithecus fossils, including the StW 573 skeleton, come from subterranean deposits [T. C. Partridge et al., Science 300, 607–612 (2003); R. J. Clarke, K. Kuman, J. Hum. Evol. 134, 102634 (2019)]. Here, we report a cosmogenic nuclide isochron burial date of 3.41 ± 0.11 million years (My) within the lower middle part of Member 4, and simple burial dates of 3.49 ± 0.19 My in the upper middle part of Member 4 and 3.61 ± 0.09 My in Jacovec Cavern. Together with a previously published isochron burial date of 3.67 ± 0.16 My for StW 573 [D. E. Granger et al., Nature 522, 85–88 (2015)], these results place nearly the entire Australopithecus assemblage at Sterkfontein in the mid-Pliocene, contemporaneous with Australopithecus afarensis in East Africa. Our ages for the fossil-bearing breccia in Member 4 are considerably older than the previous ages of ca. 2.1 to 2.6 My interpreted from flowstones associated with the same deposit. We show that these previously dated flowstones are stratigraphically intrusive within Member 4 and that they therefore underestimate the true age of the fossils.

The taxonomy, phylogeny, and chronology of Australopithecus in South Africa have long been controversial, with the site of Sterkfontein central to the debate (1–8). Fossils at the sites of Sterkfontein and Makapansgat in the Cradle of Humankind have been generally classed as Australopithecus africanus (9), but both assemblages have been recognized to include a second species (10), Australopithecus prometheus (11), with some cranial and postcanine dental morphology similar to Paranthropus, which suggested it might have been ancestral to that genus. A previous cosmogenic isochron burial date of 3.67 ± 0.16 million years (My) (2) places the A. prometheus skeleton StW 573 from the Silberberg Grotto, which is low within the Sterkfontein Formation (12), similar in age to Australopithecus afarensis at Laetoli (13) and late Australopithecus anamensis at Woranso-Mille (14). Previous burial dating in Jacovec Cavern, a separate chamber low within the Sterkfontein cave system, showed that Australopithecus fossils there are similar in age to StW 573 (1). These ages have been challenged, however, because they are much older than estimates for the Australopithecus-bearing breccia from higher in the cave (3–5). Here, we provide burial dates for these higher Australopithecus-bearing breccias. We also provide stratigraphic evidence to reconcile the relatively old ages determined from cosmogenic nuclide dates of the breccia with much younger ages determined from dating flowstones within the breccia using U-Pb and paleomagnetic dating (4, 5) at Sterkfontein.The main body of the Sterkfontein cave fills has been divided into six members (12), with Members 1 to 3 underground and Members 4 to 6 now exposed through erosion of the cave roof (12; Fig. 1). The bulk of the Australopithecus fossil assemblage was recovered from Member 4, excepting the skeleton StW 573 from Member 2 (1, 2, 11) and a small assemblage from Jacovec Cavern (1). The StW 53 cranium was assigned to a phase of infill distinct from Member 5 but of uncertain age (15), but it is now shown to be a remnant of Member 4 (16); the deposit’s fauna and age need further study because solution pockets and erosion have significantly affected the breccia. Faunal correlations with sites in East Africa generally indicate a Late Pliocene or Early Pleistocene age for Member 4 (6), although localized mixing between Member 4 and the overlying Member 5 is very likely in parts of the site and the significant stratigraphic complexity at Sterkfontein was not recognized during most of the excavations. Stratigraphic records were not kept during excavations by P. V. Tobias and A. R. Hughes from 1976, and the presence of the younger member above the Type Site where fossils were blasted out and studied by R. Broom in the 1930s and Broom and J. T. Robinson (1947 to 1949) was not recognized at that time. Electron spin resonance (ESR) dating of fossil teeth exhibits a large spread from ∼1 to 4 My (7, 8), suggesting complex uranium uptake or mixing. Due to the potential for open system behavior and evidence for later fluid flow and carbonate deposition throughout the Member 4 breccia, we consider the ESR ages unreliable.Open in a separate windowFig. 1.Map and cross section of Sterkfontein showing sample locations. (A) Map shows the extent of surface deposits and excavations superposed on the cave system. Sample locations reported here are shown as green circles; selected hominin fossils are shown with red stars and U-Pb-dated samples with yellow circles. Universal Transverse Mercator (UTM) coordinates are shown. (B) Cross section of the surface deposits along east-west red line in A. Cosmogenic sample locations are in green circles, and flowstone sample BH4-9 from ref. 5 in BH 4 is shown as a yellow circle. Measured bedding shows that the flowstone is located stratigraphically between the cosmogenic samples, although like other flowstones in Member 4, it is likely intrusive and younger than the breccia. Cross-section topography based on light detection and ranging (LiDAR) collected at the surface and underground. Borehole 4 stratigraphy is based on ref. 5.Previous radiometric dating of Member 4 has been limited to U-Pb dates of flowstone. One such flowstone in the vicinity of the discovery site of the Sts 5 cranium (OE-14 of ref. 4; Figs. 1 and ​and2)2) dates to 2.03 ± 0.06 (2σ) My. A second flowstone (BH4-9 of ref. 4), recovered from a core taken in the eastern area of the exposed M4 breccia body (borehole 4; BH4 in Fig. 1), yields an age of 2.65 ± 0.18 (2σ) My. These two flowstones have previously been considered to bracket the top and bottom of Member 4 (4, 5); when combined with magnetostratigraphy of flowstone and adjacent fine-grained deposits, they place Member 4 from 2.07 to 2.61 My (5), which is much younger than the ∼3.7-My cosmogenic age (2) for Member 2, and approaching or overlapping Paranthropus and Homo at nearby Drimolen (17), Swartkrans (18, 19), and Sterkfontein Member 5 (2) and Australopithecus sediba at Malapa (20). However, there are three main problems with this interpretation for the age of the breccia, as follows:Open in a separate windowFig. 2.Stratigraphic sections and associated photos showing previously dated flowstone. Two sections are located at red bars shown in the base map found in the figure legend. (A) North-south section shows that the previously dated flowstone OE-14 (5) is not in stratigraphic contact with Member 4 but instead is separated by fins of dolomite and decayed dolomite that were removed by blasting. Its age therefore does not constrain that of Member 4. (B) Detailed section of the OE-14 flowstone (5) shows that it lies on decayed dolomite and reworked decayed dolomite breccia derived internally within the cave. The flowstone is overlain by and interfingers with orange sandy microbreccia with no clear stratigraphic relation to Member 4 or Member 5. The north-south cross section intersects at ca. 3.5 m on the west-northwest–east-southeast section, at the plaque.

• 1)The presumed top flowstone OE-14 does not directly constrain the age of Member 4. It grew in a cavity adjacent to the cave wall and was deposited directly upon autochthonous dolomite breccia and decayed dolomite (Fig. 2). It is separated from Member 4 by a vertical fin of dolomite that was removed by blasting but is still present along strike (Fig. 2). A fine-grained, well-bedded sandy breccia interstratifies the flowstone in its upper part, but there are no diagnostic features to correlate this sandy deposit with either Member 4 or the overlying Member 5. Instead, it is more likely to be derived from a separate entrance and deposited in a small cavity near the cave roof. There is no stratigraphic evidence that this flowstone was emplaced in sequence capping Member 4.
• 2)The presumed bottom flowstone BH4-9 actually lies in the upper middle part of Member 4 rather than at its base as previously supposed (Fig. 1). This is because the inferred dip of the talus cone in ref. 4 is incorrect due to a misconception that the bouldery talus facies in Member 4 is proximal rather than distal, requiring a talus cone dipping gently southwest. As discussed below, field observations (21) indicate instead a steep dip to the northeast (SI Appendix, Fig. S1), which places the flowstone at a higher stratigraphic level.
• 3)It is likely that most or all of the flowstones in the cores are intrusive, filling dissolved postdepositional cavities, as was previously demonstrated for Member 2 (22, 23) and is common in Member 4.

Because the interpretation of the dating of Member 4 relies so heavily on the cave infill stratigraphy, we describe the depositional setting here before presenting our results.Member 4 accumulated as a talus cone within the cave, beneath a vertical entrance shaft. Cave talus cones exhibit many similarities with surface rockfall deposits (22, 23). In unconsolidated clast-rich deposits, the slope angle typically ranges between 28° and 38° (24–27). Larger and rounder rocks are transported to the flanks and toe of the cone, while smaller rocks tend to pile near the apex or become lodged in crevices (25, 26), leading to grain size segregation. In the talus proximal and medial slope, elongated clasts tend to align their long axes parallel to the talus cone bedding and glide downslope, suspended by the matrix (27). As a result, the proximal facies tends to be finer and matrix supported with bedding planes expressed in the fabric, while the distal facies tends to be more bouldery, clast supported, and open in structure (SI Appendix, Fig. S2). The edge of the talus cone typically grades into low-gradient, fine-grained sediments blanketing the cave floor (SI Appendix, Fig. S2). Relatively low-density vegetation that falls into the cave entrance commonly accumulates near the talus cone apex.The Member 4 breccia has long been recognized as an exhumed talus cone due to its steeply dipping bedding that radiates from the southern part of the surface exposures (12, 28–31). Our survey of >1,000 elongated clast orientations within the breccia confirms a dip of 42° ± 16° down to the northeast (SI Appendix, Text and Fig. S1). The presence of fossilized liana in Member 4 (32), preferentially located near the southern end of the exposed talus (15, 33), provides additional evidence for a former entrance in the south. After sedimentation of Member 4 ceased, likely due to filling of the cave and choking of the entrance, the breccia was cemented by calcite and then partially dissolved and eroded into an irregular surface including cavities within the breccia. Member 5 then entered from a separate entrance further to the east and blanketed Member 4 unconformably (Fig. 1 and SI Appendix, Fig. S1), intruding into some of the dissolved cavities.Many of the cavities that formed within Member 4 subsequent to its deposition were filled with calcite flowstone. In 1947, Haughton noted within the breccia “prominent almost horizontal but irregularly thick veins of [white calcite] which have, undoubtedly, been formed subsequent to the deposition of the breccia” (34). More recent stratigraphic analyses (2, 22, 23) showed clear evidence of intrusive flowstone formation in Member 2 in the Silberberg Grotto. Here, we document similar relationships in Member 4, in a section exposed at the western end of Fossil Cavern, down-dip of the BH4-9 sample (SI Appendix, Fig. S3). These flowstones exposed in the Fossil Cavern are without exception intrusive and younger than the breccia in which they are found, even though they can lie parallel to bedding. Evidence for their intrusive nature comes from solutional unconformable contacts, as well as blocks derived from the cemented breccia that are embedded in the calcite flowstone (SI Appendix, Fig. S3).The sedimentary fabric and architecture indicate strongly that Member 4 accumulated as a talus cone radiating from the southern edge of the exposed breccia (12, 15, 28–31). The sedimentary facies provide additional evidence for this interpretation. A finer-grained, matrix-supported facies with plant fossils (33) proximal to the entrance transitions to a bouldery, clast-supported, matrix-poor facies distally, typical of accumulation at the bottom of a shaft (22). However, a considerably different model has been presented in the literature based on interpolation among five widely separated sediment cores distributed around the periphery of the exposed breccias (SI Appendix, Fig. S4; 4, 35). The cores were correlated based on the transition from autochthonous to allochthonous material, indicating the base of the externally derived talus, as well as on the presence of flowstone layers, which were assumed to be synchronous if not continuous across the boreholes, and deposited in ascending sequence with the breccia during deposition. Several of these flowstones were dated with U-Pb and correlated across the cores (4). The sources of the breccia were then interpreted based on a longitudinal facies attribution in which coarse bouldery breccia with scant matrix was considered proximal to the cave entrance, a finer-grained matrix-supported facies medial on the talus cone, and a fine-grained, horizontally bedded facies most distal (4). The cave entrances were interpreted to be associated with the boulder facies (4), implying that Member 4 formed a gently dipping surface emanating from an entrance to the northeast. These interpretations of the proximal and medial facies are opposite of expectations on a talus cone, and a cave entrance to the northeast is diametrically opposed to the observed steep talus dip from the southwest. Moreover, the flowstones upon which the stratigraphic correlations are based (4) are most likely intrusive and younger than the breccia in which they are found and cannot be correlated across the widely separated cores. We believe that the original field-evidence-based interpretation of a talus cone emanating from the south (12, 15, 28–31) is correct.The recognition of serious stratigraphic problems with the interpretation of previous dating based on flowstones brings the true age of the Member 4 breccia and its fossils into question. Does Australopithecus in Member 4 date closer to the ∼3.7-My age of Member 2, or to the ∼2.1-My age of Paranthropus, Homo, and A. sediba (17–20)?To date the Member 4 breccia directly, we use isochron burial dating with ²⁶Al and ¹⁰Be on a suite of clasts collected from the deepest exposures in the excavation site (Fig. 1, sample ST M4 ISO). We also date a single sample of sandy matrix from the upper middle part of Member 4, collected from Fossil Cavern (Fig. 1, sample ST 10; “lower cave” of ref. 12), and a single sample of sand from Jacovec Cavern (Fig. 1, sample ST 11), supplementing previously reported data (1).     

From the Cover: Magmatic thickening of crust in non–plate tectonic settings initiated the subaerial rise of Earth’s first continents 3.3 to 3.2 billion years ago

When and how Earth''s earliest continents—the cratons—first emerged above the oceans (i.e., emersion) remain uncertain. Here, we analyze a craton-wide record of Paleo-to-Mesoarchean granitoid magmatism and terrestrial to shallow-marine sedimentation preserved in the Singhbhum Craton (India) and combine the results with isostatic modeling to examine the timing and mechanism of one of the earliest episodes of large-scale continental emersion on Earth. Detrital zircon U-Pb(-Hf) data constrain the timing of terrestrial to shallow-marine sedimentation on the Singhbhum Craton, which resolves the timing of craton-wide emersion. Time-integrated petrogenetic modeling of the granitoids quantifies the progressive changes in the cratonic crustal thickness and composition and the pressure–temperature conditions of granitoid magmatism, which elucidates the underlying mechanism and tectonic setting of emersion. The results show that the entire Singhbhum Craton became subaerial ∼3.3 to 3.2 billion years ago (Ga) due to progressive crustal maturation and thickening driven by voluminous granitoid magmatism within a plateau-like setting. A similar sedimentary–magmatic evolution also accompanied the early (>3 Ga) emersion of other cratons (e.g., Kaapvaal Craton). Therefore, we propose that the emersion of Earth’s earliest continents began during the late Paleoarchean to early Mesoarchean and was driven by the isostatic rise of their magmatically thickened (∼50 km thick), buoyant, silica-rich crust. The inferred plateau-like tectonic settings suggest that subduction collision–driven compressional orogenesis was not essential in driving continental emersion, at least before the Neoarchean. We further surmise that this early emersion of cratons could be responsible for the transient and localized episodes of atmospheric–oceanic oxygenation (O₂-whiffs) and glaciation on Archean Earth.

The emergence of continental crust above sea level (called continental emersion) critically influences atmospheric and ocean chemistry, climate, and the supply of nutrients to the oceans via weathering and fluvial runoff (1, 2). However, it remains unclear when large areas of subaerial continental crust first appeared on Earth (1–13). A rapid and extensive emersion of continental crust at the Archean–Proterozoic transition (2.5 billion years ago [Ga]) is inferred from abrupt shifts in the oxygen isotope compositions of shales and magmatic zircons, zinc isotope composition of iron formations, and an increase in subaerial continental volcanism at that time (1, 3–5, 7). However, >3.0 to 2.7-Ga-old paleosols (ancient horizons of subaerial weathering) and terrestrial sedimentary rocks that formed atop Earth''s earliest stable continental nuclei, the cratons (14–17), provide direct evidence for earlier episodes of continental emersion. This inference is further corroborated by an increase in the diversity of detrital zircon ages in clastic sedimentary rocks from ∼2.8 Ga onwards, representing the development of regionally extensive watersheds at that time (13). Thus, subaerial exposure of continental crust before 2.5 Ga seems evident. However, the exact timing and spatial extent of these emersion events are poorly constrained, and their global significance remains unclear. Moreover, the mechanisms and tectonic settings that drove continental emersion during the Archean also remain ambiguous. A uniformitarian view posits that Archean continental emersion (whether at ∼2.5 Ga or earlier) was driven by plate tectonics (1, 7, 9) with subduction-collision processes forming thick continental crust with high-standing topography via magmatism and compressional deformation, as is observed on modern Earth (2). However, the operation of plate tectonics in the Archean is disputed (9, 10, 18, 19), and a growing body of evidence suggests that subduction-collision processes were not globally prevalent until ∼2.5 to 2.0 Ga (10, 20–25), warranting the consideration of alternative mechanisms for producing subaerial continental landmasses on early Earth.Here, we integrate the Paleoarchean (3.6 to 3.2 Ga) to Mesoarchean (3.2 to 2.8 Ga) magmatic and sedimentary records of the Singhbhum Craton of India to elucidate the timing and underlying geodynamics of craton-wide emersion of continental crust in the Archean. This craton is ideal for studying Archean continental emersion as it hosts widespread Mesoarchean terrestrial to shallow-marine siliciclastic strata (26–29) and one of the oldest paleosols on Earth (the ∼3.29- to 3.08-Ga Keonjhar paleosol) (30) (Fig. 1A), providing an unambiguous record of early subaerial continental crust. We first synthesize detrital zircon data (SI Appendix, Methods and Datasets S1 and S2) from these Mesoarchean strata to determine the timing of emersion of the Singhbhum Craton. Then, we analyze the published compositional data of the craton’s Paleo-to-Mesoarchean granitoids (SI Appendix, Methods and Dataset S3) to reconstruct the history of crustal thickening and chemical maturation before and during the emersion. This allows us to link the physicochemical evolution of Archean cratonic crust to its emersion as the long-term topography of subaerial continents is critically controlled by their thick, silica-rich (less-dense) crust, which experiences large positive buoyancy and thereby a greater isostatic uplift relative to the surrounding thin and mafic (more-dense) oceanic crust (2). In particular, we determine the pressure–temperature (P-T) conditions of formation of the tonalite–trondhjemite–granodiorite (TTG) suite of granitoids—the principal crustal component of the Singhbhum Craton. The P-T data provide a time-integrated estimate of crustal thicknesses and elucidate the tectonic process controlling the craton’s emersion. These crustal thickness values are cross checked against the independent thickness estimates provided by the La-Yb systematics of the TTGs. Finally, a link between crustal thickening, maturation, and emersion is demonstrated via isostatic modeling.Open in a separate windowFig. 1.Spatial distribution and detrital zircon U-Pb ages of the Singhbhum cover sequence. (A) Simplified geological map of the Singhbhum Craton (29, 31) showing the outliers of the Singhbhum cover sequence and their granite–greenstone basement (SI Appendix, SI Text). The orange area in the Inset shows the location of the Singhbhum Craton within the Indian Peninsula. The younger (∼3.0 to 2.8 Ga) granitoids (including those of the Rengali Province) that intruded the outliers of the cover sequence are also shown. The formations comprising the outliers include: Mahagiri (Mhg), Pallahara-Mankaharchua (PM), Simlipal (Smp), Keonjhar (Kj), Birtola (Bir), Achu (Ac), Bisrampur (Brm), and Dhanjori (Dj). (B) Kernel density estimate (KDE) of <±10% discordant detrital zircon (²⁰⁷Pb/²⁰⁶Pb) ages from different outliers of the cover sequence (SI Appendix, Fig. S1). For each outlier, the white arrow shows the weighted mean ²⁰⁷Pb/²⁰⁶Pb age of the youngest detrital zircon population, which represents its maximum depositional age (SI Appendix, Fig. S1). The minimum depositional age (dashed gray line) of ∼2.94 Ga is constrained from a metamorphic event that affected the outliers. The colored bands show the age brackets of the different phases of granitoid magmatism and greenstone belt formation. Data are in Dataset S1. Refer to SI Appendix, Methods and SI Text for details.     

Two-dimensional fractal nanocrystals templating for substantial performance enhancement of polyamide nanofiltration membrane

In this study, we report the emergence of two-dimensional (2D) branching fractal structures (BFS) in the nanoconfinement between the active and the support layer of a thin-film-composite polyamide (TFC-PA) nanofiltration membrane. These BFS are crystal dendrites of NaCl formed when salts are either added to the piperazine solution during the interfacial polymerization process or introduced to the nascently formed TFC-PA membrane before drying. The NaCl dosing concentration and the curing temperature have an impact on the size of the BFS but not on the fractal dimension (∼1.76). The BFS can be removed from the TFC-PA membranes by simply dissolving the crystal dendrites in deionized water, and the resulting TFC-PA membranes have substantially higher water fluxes (three- to fourfold) without compromised solute rejection. The flux enhancement is believed to be attributable to the distributed reduction in physical binding between the PA active layer and the support layer, caused by the exertion of crystallization pressure when the BFS formed. This reduced physical binding leads to an increase in the effective area for water transport, which, in turn, results in higher water flux. The BFS-templating method, which includes the interesting characteristics of 2D crystal dendrites, represents a facile, low-cost, and highly practical method of enhancing the performance of the TFC-PA nanofiltration membrane without having to alter the existing infrastructure of membrane fabrication.

Thin-film composite polyamide (TFC-PA) membranes are widely used in reverse osmosis and nanofiltration (NF), which have extensive and continuously growing applications in water treatment, desalination, and wastewater reuse (1–4). Typical TFC-PA membranes are fabricated using interfacial polymerization (IP), which involves a polymerizing reaction between amine and acid chloride precursors at the water–oil interface (5–9). In a typical IP for producing TFC-PA NF membranes, a polyether sulfone (PES) ultrafiltration membrane is first impregnated with an aqueous solution of piperazine (PIP) and then placed into contact with a hexane solution of trimesoyl chloride (TMC). The PIP monomers diffuse across the water–hexane interface and react with the TMC to form a cross-linked dense PA film that serves as the active layer for water–salt separation (3, 8, 10). This PA film is tightly bound to the underlying PES support layer, and the way they bind to each has a strong impact on the water flux of the resulting TFC-PA membrane (11–15).Enhancing the water flux of an NF membrane without compromising its solute rejection can potentially lead to substantial savings in treatment cost and has sizable practical impacts due to the broad application of TFC-PA membranes. While extensive research (9, 10, 16–25) has been performed with the goal of performance enhancement, many promising approaches (10, 16–25) reported in the literature require significant modifications of the existing infrastructure or method of manufacturing TFC-PA membranes and thus are prohibitively complex or too expensive to implement. A desirable approach for enhancing TFC-PA membrane performance should be simple, low cost, effective, and readily integrated into the existing method of TFC-PA membrane fabrication.Herein, we report an elegant and highly practical method using two-dimensional (2D) fractal crystal dendrites to dramatically increase the water permeance of the TFC-PA NF membrane while maintaining its solute rejection performance. By adding NaCl to the aqueous PIP solution during the IP process, we observed that NaCl crystal dendrites emerged in the confinement between the PA layer and the PES support when the TFC-PA membrane was cured by heat (Fig. 1 A–C). These spectacular branching fractal structures (BFS) are considered to be 2D because they are less thick when compared with the overall size of the BFS sprawling along the plane parallel to the membrane surface. Dissolving the PES support using dimethylformamide revealed a large number of crystals adhering to the bottom of the PA film (SI Appendix, Figs. S1 and S2), confirming the position of the BFS to be between the PA active layer and the PES support. Elemental analysis using energy-dispersive X-ray spectroscopy (Fig. 1 D and E) and crystal structure analysis using X-ray diffraction (SI Appendix, Fig. S3) confirmed that these 2D BFS were indeed NaCl crystals.Open in a separate windowFig. 1.Formation process and surface morphology of BFS-templated TFC-PA membrane. (A) Schematic illustration of the process for preparing a BFS-templated TFC-PA membrane via interfacial polymerization. (B) Surface morphology of the BFS-templated TFC-PA membrane. (C) Close-up surface morphology of the BFS-templated TFC-PA membrane. (D and E) Elemental mapping images of Na (D) and Cl (E) on the surface of a BFS-templated TFC-PA membrane. (NaCl concentration in PIP solution: 8 g·L⁻¹; curing temperature: 60 °C).     

Spin crossover in ferropericlase and velocity heterogeneities in the lower mantle

Deciphering the origin of seismic velocity heterogeneities in the mantle is crucial to understanding internal structures and processes at work in the Earth. The spin crossover in iron in ferropericlase (Fp), the second most abundant phase in the lower mantle, introduces unfamiliar effects on seismic velocities. First-principles calculations indicate that anticorrelation between shear velocity (V_S) and bulk sound velocity (V_φ) in the mantle, usually interpreted as compositional heterogeneity, can also be produced in homogeneous aggregates containing Fp. The spin crossover also suppresses thermally induced heterogeneity in longitudinal velocity (V_P) at certain depths but not in V_S. This effect is observed in tomography models at conditions where the spin crossover in Fp is expected in the lower mantle. In addition, the one-of-a-kind signature of this spin crossover in the R_S/P (??ln?V_S/??ln?V_P) heterogeneity ratio might be a useful fingerprint to detect the presence of Fp in the lower mantle.Ferropericlase (Fp) is believed to be the second most abundant phase in the lower mantle (1, 2). Since the discovery of the high-spin (HS) to low-spin (LS) crossover in iron in Fp (3), this phenomenon has been investigated extensively experimentally and theoretically (4–14). Most of its properties are affected by the spin crossover. In particular, thermodynamics (14) and thermal elastic properties (15–20) are modified in unusual ways that can change profoundly our understanding of the Earth’s mantle. However, this is a broad and smooth crossover that takes place throughout most of the lower mantle and might not produce obvious signatures in radial velocity or density profiles (20, 21) (see Figs. S1 and S2). Therefore, its effects on aggregates are more elusive and indirect. For instance, the associated density anomaly can invigorate convection, as demonstrated by geodynamics simulations in a homogeneous mantle (22–24). The bulk modulus anomaly may decrease creep activation parameters and lower mantle viscosity (10, 24, 25) promoting mantle homogenization in the spin crossover region (24), and anomalies in elastic coefficients can enhance anisotropy in the lower mantle (16). Less understood are its effects on seismic velocities produced by lateral temperature variations.The present analysis is based on our understanding of thermal elastic anomalies caused by the spin crossover. It has been challenging for both experiments (15–19) and theory (20) to reach a consensus on this topic. Measurements often seemed to include extrinsic effects, making it difficult to confirm the spin crossover signature by different techniques and across laboratories. A theoretical framework had to be developed to address these effects. However, an agreeable interpretation of data and results has emerged recently (20). With increasing pressure, nontrivial behavior is observed in all elastic coefficients, aggregate moduli, and density throughout the spin crossover—the mixed spin (MS) state. In an ideal crystal or aggregate, bulk modulus (K_S), C₁₁, and C₁₂ are considerably reduced in the MS state, whereas shear modulus (G), C₄₄, and density (ρ) are enhanced. The pressure range of these anomalies broadens with increasing temperature whereas the magnitude decreases. With respect to the HS state, all these properties are enhanced in the LS state.